AI PCs and NPUs in 2026: What TOPS Actually Change

An “AI PC” is first of all a computer with a specialised accelerator, the NPU, alongside its central processor and graphics processor. The chip efficiently performs the matrix multiplication used by neural networks. It does not make every program intelligent.

CPU, GPU and NPU: three roles

The CPU remains the orchestrator and excels at varied, low-latency tasks. The GPU runs many calculations in parallel and is often still best for a large model or creative work. The NPU targets sustained AI workloads at low power: video blur, framing, noise removal, transcription or small local models.

Software must explicitly support the accelerator. If an app uses only the cloud or GPU, a more powerful NPU may sit idle.

What does a TOPS measure?

TOPS means trillions of operations per second. It describes theoretical throughput at a given precision, often INT8. It cannot fairly compare two architectures without the model, memory, software and power budget.

NPU TOPS must also be separated from combined CPU + GPU + NPU figures. Microsoft sets a threshold above 40 NPU TOPS for its Copilot+ PC category, alongside memory and storage requirements. A vendor may advertise 120 “platform TOPS” while the NPU delivers only part of them.

What can run locally

Local processing reduces latency and may keep some data on the device. Common functions include webcam effects, captions, semantic search, lightweight image generation and limited assistants. Larger models depend more on memory capacity and bandwidth, then GPU performance.

“Local” does not guarantee privacy: an app can still synchronise data. Check its settings, policy and network behaviour.

Memory often matters more than the NPU

A generative model's weights must fit in memory and move quickly. Sixteen gigabytes is enough for ordinary work but becomes tight with creation, virtual machines or local models. Thirty-two gigabytes provides sensible headroom; demanding professional work may justify more.

Soldered memory that cannot be upgraded should be chosen for several years. Storage, display, keyboard, cooling and battery still matter more in daily use than an AI badge.

Should you replace your PC?

Not for the NPU alone. If your computer is fast, efficient and compatible with your software, cloud AI does not require new hardware. An AI PC makes sense during a normal replacement cycle, for heavy video conferencing, accessibility tools, supported creative apps or energy-efficient local computation.

Compare complete testing: real battery life, noise, unplugged performance, display, repairability and your own apps. TOPS is one row in the table.

The verdict: the NPU is becoming a useful standard component, much like the video encoder before it. Its value depends on software. To turn these principles into a purchase, read our AI laptop buying guide.